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sensitivitymult  

Sensitivity Analysis for Observational Studies with Multiple Outcomes
View on CRAN: Click here


Download and install sensitivitymult package within the R console
Install from CRAN:
install.packages("sensitivitymult")

Install from Github:
library("remotes")
install_github("cran/sensitivitymult")

Install by package version:
library("remotes")
install_version("sensitivitymult", "1.0.2")



Attach the package and use:
library("sensitivitymult")
Maintained by
Paul R. Rosenbaum
[Scholar Profile | Author Map]
First Published: 2017-05-16
Latest Update: 2017-08-29
Description:
Sensitivity analysis for multiple outcomes in observational studies. For instance, all linear combinations of several outcomes may be explored using Scheffe projections in the comparison() function; see Rosenbaum (2016, Annals of Applied Statistics) . Alternatively, attention may focus on a few principal components in the principal() function. The package includes parallel methods for individual outcomes, including tests in the senm() function and confidence intervals in the senmCI() function.
How to cite:
Paul R. Rosenbaum (2017). sensitivitymult: Sensitivity Analysis for Observational Studies with Multiple Outcomes. R package version 1.0.2, https://cran.r-project.org/web/packages/sensitivitymult. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0.1 (2017-05-16 23:50)
Other packages that cited sensitivitymult R package
View sensitivitymult citation profile
Other R packages that sensitivitymult depends, imports, suggests or enhances
Complete documentation for sensitivitymult
Functions, R codes and Examples using the sensitivitymult R package
Some associated functions: amplify . artcog . comparison . mscorev . planScheffe . principal . senm . senmCI . separable1v . tbmetaphase . teeth . 
Some associated R codes: amplify.R . comparison.R . mscorev.R . planScheffe.R . principal.R . senm.R . senmCI.R . separable1v.R .  Full sensitivitymult package functions and examples
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